RGB Color System Research Articles

Superhydrophobic Paper Strips with Embedded Agarose-Anthocyanin Mini-Discs for Point-of-Need Quantitative pH Measurements.

Commercial pH paper is a quick and simple tool for measuring a solution's acidity/basicity, but it only provides qualitative or semi-quantitative results, and the synthetic indicator dyes within can be toxic or carcinogenic. Although pH meters enable more accurate and quantitative analysis, they are less convenient to operate and are tedious to calibrate. This presents a need for an alternative pH testing method for applications where it is not easy or possible to use a pH meter, yet quantitative results are desired. We report herein the fabrication of a pH test strip made from superhydrophobic paper and agarose-anthocyanin film discs. In the proposed method, test strips are dipped into samples and then imaged with a portable scanner (or a smartphone). The color of the film is extracted with ImageJ software (or a mobile app), using the RGB color system. By generating a calibration curve relating the film color to the sample pH using standard buffer solutions, we are able to quantify the pH of beverages and other liquids with an accuracy and precision comparable to that of a pH meter. The test strips offer the same convenience as conventional pH paper, with the added capabilities of quantitation and multiplexed testing, which presents a practical tool for point-of-need pH analysis.

Color Modifications of a Maxillofacial Silicone Elastomer under the Effect of Cigarette Smoke.

Although it is known (from the observations of medical professionals) that cigarette smoke negatively affects maxillofacial prostheses, especially through staining/discoloration, systematic research in this regard is limited. Herein, the color modifications of M511 maxillofacial silicone, unpigmented and pigmented with red or skin tone pigments, covered with mattifiers, or with makeup and mattifiers, and directly exposed to cigarette smoke, were investigated by spectrophotometric measurements in the CIELab and RGB color systems. The changes in color parameters are comparatively discussed, showing that the base silicone material without pigmentation and coating undergoes the most significant modifications. Visible and clinically unacceptable changes occurred after direct exposure to only 20 cigarettes. By coating and application of makeup, the material is more resistant to color changes, which suggests that surface treatments provide increased protection to adsorption of the smoke components. The dynamic water vapor sorption (DVS) measurements indicate a decrease of the sorption capacity in pigmented versus unpigmented elastomers, in line with the changes in color parameters.

Detecting Defect in Central Pivot Irrigation System using YOLOv7 Algorithms

Central Pivot Irrigation System (CPIS) is a significant method for intelligent irrigation used in global agriculture. It is used to cultivate important crops like wheat, which contribute to global food security. However, the CPIS encounters technical issues that result in malfunctions in its automatic control system, leading to damage to the primary pipes and towers. This can result in significant material losses for farmers and their crops. Repairing the system is also a time-consuming process. To address this issue, a study was conducted using YOLO algorithm which contains several models, and this study used the Yolov7 models to detect defects in the CPIS machine accurately. The study used a dataset gathered from agricultural areas in Salah al-Din Governorate. The models were used to determine whether the CPIS was in a safe or dangerous state. The RGB color system with Yolov7x achieved a 95% detection rate with an accuracy, F1-score, and precision values of 0.798 and 0.954. Similarly, Yolov7x achieved a 93% detection rate with accuracy, F1-score, and precision values of 0.77 and 0.932 in the Grayscale color system. Based on the outcome, this study can conclude that the yolov7x model with RGB Color System accurately detects the CPIS in both its safe and dangerous states. This makes them useful in real-time systems for CPIS defect monitoring and control.

Analysis of Cross Validation on Classification of Mangosteen Maturity Stages using Support Vector Machine

This study explores the efficacy of the Support Vector Machine (SVM) method in classifying mangosteen fruit images based on six ripeness levels. Employing SVM enables nonlinear data classification and simultaneous utilization of multiple feature extractions, resulting in enhanced accuracy. Analysis reveals that models integrating three feature extractions outperform those with only two. With ample training data and optimized parameters, SVM achieves detection accuracy exceeding 90%. However, algorithmic enhancements are necessary to compute RGB color index values for all pixels on mangosteen skin surfaces, possibly through circular-shaped windows approximating the fruit's contour. Moreover, comparative assessments of RGB color system calculations against alternative systems such as HSI are crucial for selecting the most suitable color model in alignment with human perception.

From Simple Packaging Materials to Smart Sensors: Sunlight Exposure Sensing in Bubble Wraps Incorporating a Layered Metal Selenide Photocatalyst

AbstractThis work demonstrates that the packaging material commonly called “bubble wraps” (Aeroplast) can be leveraged to serve as a probe to visible sunlight exposure. This probe relies on a newly developed layered metal selenide photocatalyst with the general formula (DMAH)2xMnxSn3–xSe6 (DMSe‐1) (x = 1.3–1.7; DMAH+ = dimethylammonium), featuring a narrow bandgap of 0.76 eV, in addition to an indicator dye and a reducing agent. The photochemically sensitive probe is introduced into the air‐filled compartments of bubble wraps and undergoes photocatalytic degradation, resulting in a chromatic response to sunlight exposure. The probe's sensitivity to variable irradiation doses can be adjusted by varying the amount of the photocatalyst. The color intensity correlates with the absorbed irradiation dose, allowing for qualitative assessment by the naked eye or quantitative measurement using the RGB color system. The results obtained from the new probe agree with those obtained from standard sunlight pyranometers (r = 0.98), with an average error of <15%. This suggests that beyond their use as protective coatings, bubble wraps can be successfully repurposed as visible light sensors. Furthermore, this study describes the initial use of metal chalcogenides as visible light probes, potentially paving the way for the development of innovative light‐sensitive materials.

A digital image-based colorimetric method for measuring free acidity in edible vegetable oils

The standard method used to quantify free acidity (FA) in vegetable oil is neutralization titration, which requires many toxic chemicals and depends on an analyst's experience in detecting endpoints. Here, a digital image colorimetry (DIC) method using a smartphone camera was developed to measure FA in vegetable oils. A cupric acetate solution was used to produce the colorimetric reaction. The coloured solutions were imaged, and R values (from the RGB colour system) were calibrated against the respective FAs in the standards. The FA values of the samples were determined by standard addition calibration. These results were compared to measurements of FA obtained by the standard titrimetric method. An excellent correlation was obtained, with an R2 of 0.98 and a mean absolute error of 0.06%. The chemicals needed for analysis were reduced by approximately 90%. Thus, DIC is a less subjective and more economical method for determining FA in vegetable oils.

CHARACTERISATION AND ALGORITHMS FOR MONITORING THE TECHNICAL CONDITION OF BUSES BY RGB SYSTEM PARAMETERS

The algorithms of pre-trip control of buses’ technical condition under the conditions of hypothetical application of an automated system based on video registration in ATP are considered. The authors analyse the regularities of changes in the parameters of the technical condition of buses as a function of their appearance estimated by the RGB colour system parameters. Typical examples of processing and analysing static and time-varying images are given. Initial, permissible and limit values of diagnostic parameters in RGB system are defined for separate systems of buses (external lights, tyres, windscreen).
 Purpose. Determination of regularities of changes in the parameters of the technical condition of buses as a function of their appearance assessed by the parameters of the RGB color system.
 Method or methodology of the work. The method of estimating the RGB colour parameters of the reference and actual bus images in the Adobe Photoshop software environment and their subsequent mathematical analysis was used in this work.
 Results. Initial values of diagnostic parameters, limits and acceptable ranges are obtained.
 Scope of the results. The obtained results are expedient for application at creation of the automatic system of control of technical condition of the vehicle before the trip on the basis of video registration.

IMAGING ANALYSIS IN AGRICULTURAL LAND SURFACE CHARACTERIZATION - CASE STUDY ON WHEAT STUBBLE

The study used imaging analysis (UAV images) to analyze and characterize an agricultural land area resulting from the harvest of the wheat crop. The researches were carried out in the framework of ARDS Lovrin, agricultural year 2021-2022. The agricultural land was worked with a disk, and the vegetable remains (straw, stubble) were partially incorporated into the soil. The images were taken with the drone (DJI Phantom 4) at variable heights, between H = 0.5 m and H = 50 m from the ground level (19 series of images from variable heights). The analysis of the images resulted in values in the RGB color system. Normalized values (rgb) and NDI and INT indices were calculated. The color parameter R (red) varied between R = 77.36 – 89.14±0.71, the color parameter G (green) varied between G = 71.29 – 81.99±0.60, and the color parameter B (blue) varied between B = 71.42 – 79.29±0.47. The values of the calculated indices varied between NDI = 0.040 – 0.048±0.0007, respectively INT = 73.357 – 83.217±0.582. Correlations of varying levels of intensity were recorded between color parameters, calculated indies and image retrieval height. High variability was recorded in the case of the NDI index (CV = 7.3156), and low value in the case of the normalized value g (CV = 0.4443). Polynomial equations described the variation of some color parameters in relation to the image retrieval height (p<0.001). The variation of the NDI index in relation to the image acquisition height was described by a spline model, under statistical safety conditions ( ). Associated with the image retrieval height, the NDI index presented four ranges of values, respectively uniform values on the 0.5 - 1 m height interval, and on the 25 - 50 m height interval; variation of 0.001 units on the height interval 2 - 8 m, and high variability on the height interval 9 - 20 m.

Comparative Evaluation of Hue Value Chroma using Cross Polarised Photography

Introduction: Digital photographs offer a wide range of colour options. They aid in increasing communication between a dentist and a technician by making the morphology, colour, and texture of the teeth easier to visualise. A polarising filter reduces reflections and glare while boosting colour saturation in an image. The aim of the study was to analyse images with and without polarised photography. Methodology: A total of 125 images of shade guidelines were collected for this study, 5 each shade tab for 5 shades (A1 to A4). We looked at the following shade guidance systems: VITA Classical (VITA Zahnfabrik) (control), IPS e. max Ceram (Ivoclar Vivadent) were photographed with a Canon EOS 60D digital camera and a 100-mm Canon Macro Lens. Ambient light, exposure (1/125, f16), ISO (100), flash (ETTL), distance, focusing (1:1), and backdrop were all standardized in the photographs. The Adobe RGB colour system was utilised since it covers nearly half of the Lab colour space. Results: Mean and standard deviation values of images with and without cross polarised photography were compared. Hue, value, chroma of the images were assessed showing no statistical difference among the images with and without cross polarised photography. Conclusion: Compared to visual and digital photographic approaches for choosing shades, the application of polarising filters had negligible effect on shade choice. When routinely practised, shade matching can improve a clinician's ability to choose the appropriate shade. Thus, knowledge and training may help someone become better at shade matching. Keywords: Hue, value, chroma, cross polarised photography, Camera, Ring flash, Micro lens.

Exploiting digital images and videos for urea determination in milk based on enzymatic hydrolysis monitoring

As an endogenous species and a milk adulterant, urea determination is important for quality control in dairy industry. This work proposes a novel, simple, and cost-effective method to determine urea by the analysis of digital images and videos. Urea hydrolysis under urease catalysis releases ammonia and the increase in pH makes feasible the photometric measurements based on the dissociation of the phenol red acid-base indicator. Digital images were acquired by a smartphone camera under controlled conditions and intensities of the reflected radiation were converted to the RGB color system using a free app (PhotoMetrix®). Digital videos were exploited for procedure optimization and evaluation of matrix effects from RGB values obtained with ImageJ® software. A linear response was achieved within 2.0–25.0 mg L-1 urea (R2 =0.996), with a coefficient of variation (n = 10) of 1.6%, and limits of detection (95% confidence level) and quantification of 0.5 and 1.5 mg L-1, respectively. Recoveries from 95% to 112% were estimated from samples spiked with urea and results for commercial milk samples achieved by the standard additions method agreed with the reference values at the 95% confidence level. The procedure is applicable to whole, semi-skim, and skim milk either processed using pasteurization or under ultra-heat treatment.

An automated method to analyze root filling voids and gaps using confocal microscopy images.

This study evaluated the feasibility of an automated method to delimit the required area to quantitatively analyze root filling voids and gaps from cross-sectional confocal laser scanning microscopy (CLSM) images. Root canals of maxillary canines were prepared with rotary instruments and filled by lateral compaction technique using gutta-percha and AH Plus sealer. The roots were stored (100% humidity, 37°C) for a period of 24h and then transversally sectioned to obtain 2-mm-thick slices from the apical and middle thirds. The areas corresponding to filling materials, gaps, and voids were manually delimited or automatically demarked by ImageJ software after converting the images to the RGB color system. Based on manual and automatic delimitations, the percentages of voids and gaps were calculated. Data of voids and gaps between middle and apical thirds were individually compared by paired t-test. Pearson`s correlation test was used to assess the correlation of data between the methods. Irrespective of the method of area delimitation, no difference was observed between the root thirds for both voids and gaps, while the p-values calculated for each method were similar. Almost perfect correlations between the methods were observed for both outcomes. The proposed method to automatically delimit the areas corresponding to filling material, voids, and gaps appears to be a valid method to facilitate the quantitative analysis of defects in root canal fillings using topographic CSLM images.

Zenopontonia soror caridean shrimp exhibits dynamical mimicry with sea star host switching

Zenopontonia soror (Nobili, 1904) (Caridea: Palaemonidae) is a shrimp symbiont of several sea star species that exhibits homochromy with distinct mimetic coloration according to host species. To date, populations of Z. soror have been studied extensively in the Indo-Pacific and Gulf of Panama; however, those present in the Gulf of California (Mexico) have not been evaluated. Here we conduct the first evaluation of the diversity of chromotypes present in Z. soror populations in Bahía de La Paz (Baja California Sur, Mexico), and experimentally tested how long shrimp take to archieve mimicry post sea star switch. We hypothesized that Z. soror individuals rapidly change coloration (minutes to few hours) throughout their ontogeny to mimic the coloration of host species to decrease risk of predation. This hypothesis was tested by translocating Z. soror individuals to a different sea star species with different coloration and background in the field and under laboratory conditions for three consecutive days. At least 18 chromotypes of Z. soror were identified among 386 observed specimens based on the RGB color system; and colors were independent of body size. Each chromotype holds different relative abundance in the population. Coloration was not distinctive of each individual, while color intensity increased along ontogeny development from semi-transparent (juveniles) to solid coloration (adult phase). Dynamic contraction or dispersion of the chromatophores (pigment migration) caused changes in coloration to resemble coloration of the basibiont sea star. Full mimicry of new host was achieved within 36 h in field and laboratory conditions. Zenopontonia soror individuals were observed to mimic the white spines of the sea star host Acanthaster solaris by exhibiting a white dorsal band, while others selected color-concealing hosts to stay cryptic for a short time. We conclude that Z. soror dynamically shifts coloration as an adaptation to match the symbiont shrimp–sea star host coloration to minimize or prevent predation, but individuals are vulnerable to be detected by visual predators during the color transition (<36 h period). The combined use of the Hogben and Slome index and the RGB color system from digital images provide the most precise method to assign intensity and color in epibiont-host organisms to understand the complex process of homochromy.

Evaluation of Different Methods and Models for Grass Cereals’ Production Estimation: Case Study in Wheat

Adequate management of agricultural crops requires, among other things, accessible and sufficiently accurate methods for assessing plant nutrition and crop vegetation status and for agricultural production estimation. Sustainable technologies are based on correct decisions, prompt interventions and appropriate works, and correct information in real time, and the obtaining information methods can be simple, accessible, and appropriate in relation to different user categories (e.g., farmers, researchers, decision makers). This study used mineral fertilization (NPK), with 11 experimental variants, to ensure a controlled differentiated nutrition of the wheat plants, “Alex” cultivar. Regression analysis was used to obtain models in estimating wheat production, by methods based on: (a) NPK fertilizers applied (F) in the 11 experimental variants; (b) physiological indices (PI), represented by the chlorophyll content (Chl), and plant nutrition status on the experimental variants, in terms of macroelement content in the leaves, evaluated by foliar diagnosis (Nfd, Pfd, Kfd); (c) imaging analysis (IA) based on digital images of the wheat experimental variants, and calculated indices. A set of models was obtained, with different precision levels and statistical safety: R2 = 0.763, p = 0.013 for the model based on applied fertilizers (NPKF); R2 = 0.883, p &lt; 0.01 for the model based on foliar diagnosis (NPKfd); R2 = 0.857, p &lt; 0.01 for the model based on chlorophyll content (Chl); R2 = 0.975, p &lt; 0.01 for the model based on normalized rgb color parameters (RGB color system); R2 = 0.925, p &lt; 0.01 for the model based on the DGCI calculated index. The model based on applied fertilizers (F model) was tested in relation to wheat production data, for a period of six years, communicated by other studies. Fit degree analysis between predicted yield based on the F model and real yield (six-year average) was confirmed by R2 = 0.717, compared to R2 = 0.763 for the F model in this study. The models obtained in this study, related to the “Alex” wheat cultivar, can be used for other studies, but with a certain margin of error, given the coefficient values, specific to the obtained equations. The approach concept, methods, and models presented can be opportunities for other studies to facilitate their comparative analysis, their adaptation, and/or development in the form of new models that are useful in different studies, research, or agricultural practices, for their integration into crop management strategies.

A cost-effective microfluidic device for determination of biodiesel content in diesel blends

The increasing production and extensive use of biodiesel in the latest years call for the development of fast and cost-effective procedures for point-of-care analysis. One of the main quality parameters is the biodiesel content in diesel blends, which needs to conform to regional legislations. In this work, a microfluidic device exploiting chemical derivatization of alkyl esters and detection by smartphone-based digital-image colorimetry was developed. It was designed to ensure proper experimental conditions for chemical derivatization, including reagent release, and photometric measurements. Analytes reacted with alkaline hydroxylamine yielding the corresponding alkyl hydroxamates, measured as colored Fe(III) complexes. Analytical response was based on the measurement of the G (green) channel from RGB color system. By taking methyl linoleate as a model compound, a linear response was obtained from 0.1% to 0.6%(v/v) (Analytical signal = 69.6 +2.1 C, r = 0.999), coefficient of variation (n = 10) of 4.0% and limit of detection (99.7% confidence) of 0.04%(v/v). Procedure consumes 1.2 µL of sample, 230 µg of hydroxylamine, 480 µg of NaOH, 14 µg of Fe(III) and equivalent to 1.2 µL of 69%(v/v) HNO3. Accurate results were achieved in relation to the MIR reference method, with agreement at the 95% confidence level.

A Histogram-Based Technique for Simultaneous Colorimetric Determination of Malachite Green and Brilliant Green Using Triton X-100 Micelle.

Malachite green (MG) and brilliant green (BG) are two synthetic triphenylmethane dyes with applications in the textile and aquaculture industries. They are considered to be environmental contaminants due to their carcinogenic and mutagenic properties. Both dyes have the same bluish-green color in aqueous solutions. The aim of this study is to develop a colorimetric analysis as a very simple and cost-effective method to determine the residues of MG and BG simultaneously in aqueous industrial samples. This method is based on the alterations in red, blue, green (RGB) color histograms of the dyes in the presence and absence of Triton X-100 micelle. The images of the samples were taken by a digital camera and converted to the RGB color system using MATLAB software. Partial least-squares regression as a powerful chemometrics tool was used for multivariate calibrations and quantitative measurements. The performance of the proposed method was compared with a simple spectrophotometric method as a reference. Relative errors of prediction for colorimetric and spectrophotometric analysis, respectively, in micellar media were 6.56 and 4.61% for MG and 6.38 and 5.24% for BG. The shortest linear ranges for colorimetric and spectrophotometric analysis, respectively, in micellar media were 0.1-10 and 0.5-5 mg/L for MG and 0.1-15 and 0.5-6 mg/L for BG. The recovery percentages obtained from the analysis of the dyes in real samples of fish-pond water and textile wastewater ranged between 91 and 107%. The good correlation between the results of the colorimetric analysis and the spectrophotometric analysis indicates the reliability of the proposed colorimetric method. Also, the results of the relative recovery study showed insignificant matrix effect. This study demonstrates the ability of the colorimetric analysis coupled with chemometrics tools for simultaneous determination of the analytes even with nearly identical colors.

Exploiting microdistillation and smartphone-based digital-image colorimetry for determination of protein in foods

Because of their nutritional importance and industrial interest, determination of proteins is usual in food quality control. The Kjeldahl method, the most usual for protein determination and a reference to other indirect methods, is time-consuming and generates significant amounts of waste. Aiming to circumvent these drawbacks, this work proposes a simple, cost-effective, and more environmental friendly procedure based on microdistillation of the ammonium from Kjeldahl digests, absorption on an acid-base indicator solution, and digital-image colorimetry for protein determination in food. Microdistillation was carried out in a simple and inexpensive lab-made apparatus. The digital images were acquired by a smartphone camera under controlled illumination and the intensity of the reflected radiation was converted to the RGB color system using a free app (PhotoMetrix®). Measurements were based on the color change of phenol red from yellow to pink and the G channel (corresponding to the complementary color of the dissociated indicator) was taken as analytical response. A linear response was achieved within 5.0–50.0 mg/L ammonium, equivalent to 0.003–0.03 % protein (r = 0.996), as confirmed by the lack-of-fit test at the 95 % confidence level. Coefficient of variation (n = 10) and limit of detection (99.7 % confidence level) were estimated at 2.3 % and 2 mg kg−1 protein, respectively. A sample throughput of 12 h−1 was achieved with simultaneous sample processing. Protein amounts determined in foods of animal (milk) and vegetal (beans and lentils) origin yielded results in agreement with the micro-Kjeldahl reference procedure at the 95 % confidence level.

A novel approach for lactose determination in cow's milk exploiting smartphone-based digital-image photometry.

Lactose, the main carbohydrate in cow's milk, may cause health problems for consumers with intolerance. Lactose determination in milk is hindered by the matrix complexity and lack of chromophore groups. Chromatography, volumetric, and spectrophotometric approaches involving chemical derivatization are time-consuming and require laborious sample preparation, which is incompatible with the high analytical demand. In this context, a novel approach is presented for lactose determination in milk exploiting smartphone-based digital-image photometry. It was based on a modification of the Benedict's method, involving formation of the violet Cu(I)/2,2'-biquinoline-4,4'-dicarboxylate (BCA) complex instead of the copper(I) oxide precipitate, aiming at improvement of sensitivity and precision. Sample pretreatment and analyte derivatization were performed in Eppendorf tubes with minimal reagent amounts and a smartphone camera was used for image acquisition under controlled conditions. Measurements were based on the RGB color system, taking channel G as the analytical response because of the complementarity with the color of the complex. Under the optimized conditions, the proposed procedure yielded a linear response up to 20 mg L-1 (r = 0.999), with a limit of detection of 1.5 mg L-1, which is compatible with determination of lactose in milk and dairy products categorized with low content of the sugar. The procedure takes less than 10 min, with a coefficient of variation of 3.0% (n = 12) and consumes as low as 160 μg Cu and 430 μg BCA per determination, thus being a more practical, fast, cost-effective, and environmental friendly analytical method.

Recognition of arable soils from photographs obtained as part of crowdsourcing technologies

The study focuses on the possibilities of using photographs obtained using crowdsourcing technologies for the operational inventory of arable soils. The object of the study is the spectral reflectance of the open surface of arable soils of the test plots, measured using a HandHeld-2 spectroradiometer operating in the range of 325–1 075 nm, and their image in photographs taken with conventional cameras. Test sites are located in the Tula, Moscow and Tver regions. The soils of the test plots are sod-podzolic, gray forest, and leached chernozems. Based on the analysis of photographs of the surface and information obtained using a spectroradiometer, a set of spectral parameters in the RGB, YMC and HSI color systems, as well as their ratios (45 parameters), was calculated. These parameters were used to separate the analyzed soil types using classification trees. The accuracy of classification based on the results of validation varies from 63–100%. At the same time, the parameters of the HSI and YMC color systems turned out to be more informative than the parameters of the RGB color system. The established classification rules can later be used to determine the classification position of soils from images collected using crowdsourcing technologies.

Innovative prediction of milk microbiological quality from pH measurements by digital imaging photometry

A novel colorimetric assay was proposed to predict microbiological contamination of milk from pH measurements. It was based on the adsorption of the acid−base indicator phenol red to milk proteins, with the color of the suspension monitored by smartphone-based photometry through the RGB color system. Sample throughput of 30 measurements h−1, relative standard deviation of 2.0 % (n = 20), cost-effectiveness, low waste generation (570 µL per determination), and a broad analytical range (5.4 ≤ pH ≤ 7.2) were achieved. The procedure was applied for pH determination in raw and processed milk samples and the results agreed with near-infrared spectroscopy and potentiometric reference procedures at the 95 % confidence level. Relative errors were lower than 2.0 % with recoveries from 97 % to 106 %. A screening approach based on the analytical responses at G and B channels yielded the correct classification of samples masked with ammonium chloride, sodium hydroxide, urea, or formaldehyde, as well as acid and diluted milk, even when the pH of non-conforming samples was adjusted to the expected values (pH from 6.60 to 6.80). This advantage in relation to potentiometric pH measurements demonstrates the potentiality of the proposed approach for evaluation of microbiological contamination of milk.

Pocket-sized sensor for controlled, quantitative and instantaneous color acquisition of plant leaves

The color of plant leaves can be assessed qualitatively by color charts or after processing of digital images. This pilot study employed a novel pocket-sized sensor to obtain the color of plant leaves. In order to assess its performance, a color-dependent parameter (SPAD index) was used as the dependent variable, since there is a strong correlation between SPAD index and greenness of plant leaves. A total of 1,872 fresh and intact leaves from 13 crops were analyzed using a SPAD-502 meter and scanned using the Nix™ Pro color sensor. The color was assessed via RGB and CIELab systems. The full dataset was divided into calibration (70% of data) and validation (30% of data). For each crop and color pattern, multiple linear regression (MLR) analysis and multivariate modeling [least absolute shrinkage and selection operator (LASSO), and elastic net (ENET) regression] were employed and compared. The obtained MLR equations and multivariate models were then tested using the validation dataset based on r, R2, root mean squared error (RMSE), and mean absolute error (MAE). In both RGB and CIELab color systems, the Nix™ Pro color sensor was able to differentiate crops, and the SPAD indices were successfully predicted, mainly for mango, quinoa, peach, pear, and rice crops. Validation results indicated that ENET performed best in most crops (e.g., coffee, corn, mango, pear, rice, and soy) and very close to MLR in bean, grape, peach, and quinoa. The correlation between SPAD and greenness is crop-dependent. Overall, the Nix™ Pro color sensor was a fast, sensible and an easy way to obtain leaf color directly in the field, constituting a reliable alternative to digital camera imagery and associated image processing.